Data interoperability and privacy schemes in healthcare data using Blockchain technology

Abstract. Electronic Health/Medical Records (EHR/EMR) lay the foundation for securely maintaining medical records. The traditional EHR systems are not effectively managed data manipulation, delayed communication, trustless data storage, data cooperation, and distribution. Blockchain technology can play a major role in healthcare cases. This is because it uses decentralized distributed ledgers to securely manage all parties within the network. It also handles individual data through smart contracts, which can be pre-programmed by the patient for access and maintenance of healthcare data. This thesis focuses on exploring the blockchain in digital healthcare services such as Electronic Health/Medical Records (EHR/EMR). Blockchain-based implementations of Ethereum allow patients to store their medical data with smart contracts that can perform activities such as Registration, Data Append, and Data Retrieve. The challenges faced during the implementation of blockchain protocols are discussed and analyzed in the scope of finding sustainable solutions to develop secure and reliable operation

The roadmap to healthcare digitalization: factors that affect the Portuguese approach to ehealth

Healthcare systems worldwide need to improve health outcomes while reducing costs. Increasing demand for chronic disease management, such as pulmonary disease, is driving digital transformation in healthcare. The Kata® inhalation app aims to improve patients' inhalation techniques through a data-based algorithm. This study aims to classify Portugal’s proneness to healthcare digitalization. Specifically, it investigates to which extent Portugal is lagging compared to digital pioneers and how it can keep up with advancements in a rapidly evolving technological world. The results suggest that Portugal is a positive example of eHealth but its main challenges are patients’ low digital trust and inoperability across infrastructures and health subsystems

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Harmonizing Regulatory Regimes for the Governance of Patient-generated Health Data

Patient-generated health data (PGHD), created and captured from patients via wearable devices and mobile apps, are proliferating outside of clinical settings. Examples include sleep trackers, fitness trackers, continuous glucose monitors, and RFID-enabled implants, with many additional biometric or health surveillance applications in development or envisioned. These data are included in growing stockpiles of personal health data (PHI) being mined for insight by health economists, policy analysts, researchers, and health system organizations. Dominant narratives position these highly personal data as valuable resources to transform healthcare, stimulate innovation in medical research, and engage individuals in their health and healthcare. Large tech companies are also increasingly implicated in these areas, through mobile health application sales and data acquisitions. Given the many possible uses and users for PGHD, ensuring privacy, security, and equity of benefits from PGHD will be challenging. This is due in part to disparate regulatory policies and practices across technology firms, health system organizations, and health researchers. Rapid developments with PGHD technologies and the lack of harmonization between regulatory regimes may render existing safeguards to preserve patient privacy and control over their PGHD ineffective, while also failing to guide PGHD-related innovation in socially desirable directions. Using a policy regime lens to explore these challenges, we examine three existing data protection regimes relevant to PGHD in the United States that are currently in tension with one another: federal and state health-sector laws, regulations on data use and reuse for research and innovation, and industry self-regulation of consumer privacy by large tech companies. We argue that harmonization of these regimes is necessary to meet the challenges of PGHD data governance. We next examine emerging governing instruments, identifying three types of structures (organizational, regulatory, technological/algorithmic), which synergistically could help enact needed regulatory oversight while limiting the friction and economic costs of regulation that may hinder innovation. This policy analysis provides a starting point for further discussions and negotiations among stakeholders and regulators to do so

INTEGRATION OF INTERNET OF THINGS AND HEALTH RECOMMENDER SYSTEMS

The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch are presented in this research. Along with IoT in smart healthcare, Health Recommender Systems integration with IoT is important. Main Recommender Systems including Content-based filtering, Collaborative-based filtering, Knowledge-based filtering, and Hybrid filtering with machine learning algorithms are described for the Health Recommender Systems. In this study, a framework is presented for the IoT-based Health Recommender Systems. Also, a case is investigated on how different algorithms can be used for Recommender Systems and their accuracy levels are presented. Such a framework can help with the health issues, for example, risk of going to see the doctor during pandemic, taking quick actions in any health emergencies, affordability of healthcare services, and enhancing the personal lifestyle using recommendations in non-critical conditions. The proposed framework can necessitate further development of IoT-based Health Recommender Systems so that people can mitigate their medical emergencies and live a healthy life

Implementation model of an integrated blockchain and IOT system to healthcare ecosystem

Mestrado em Gestão de Sistemas de InformaçãoNo cenário de transformação digital em que estão inseridos todos os setores de atividade, para melhorar a eficiência, a produtividade e reduzir o tempo e os custos, é necessário investir em novas tecnologias. Novas tecnologias como Internet of Things (IoT) e Blockchain são desenvolvidas para melhorar a eficiência de processamento, a criação de oportunidades de negócios, a regulamentação de requisitos, a segurança e transparência e descentralização de informações, e provavelmente serão as próximas tecnologias disruptivas que transformaram os diversos setores de atividade. Por sua vez, o setor saúde tem enfrentado dificuldades com o surgimento de novas doenças e precisa se transformar e se reinventar para manter sua legitimidade e continuar cumprindo suas obrigações para com os cidadãos. A implementação de novas tecnologias acaba sendo uma das abordagens mais eficazes para aumentar a eficiência, segurança, gerenciamento, análise de big data e performance dos dados. Devido a isso, este projeto propõe um modelo de framework Blockchain e IOT aplicada a saúde. A implementação engloba a criação de um aplicativo (i.e., pacientes) e um site (i.e., médicos, hospitais, farmácias, saúde publica), os dados partilhados pelos usuários são armazenados no blockchain conectado ao aplicativo e o acesso ao Blockchain é liberado por smartcontracts. O objetivo do modelo proposto é que os dados sejam descentralizados e possibilita o acesso a todos os conectados ao blockchain. E para não infringir a proteção dos dados pessoais dos pacientes, foi tomado o cuidado de que o usuário paciente seja o “proprietário” de todos os seus dados e compartilhe-os com qualquer entidade de saúde que deseja. Para atingir os objetivos mencionados, foi definida uma metodologia de validação por conceito do modelo proposto. A validação do conceito do modelo foi dividida em cinco etapas, seguida da análise qualitativa das entrevistas semiestruturadas realizadas com pacientes, médicos e gestores de saúde. Como resultado da validação por conceito foi observado que a opinião de todos os entrevistados é que a implementação do modelo proposto é vantajosa e poderá contribuir com avanços no setor saúde. Portanto, uma vez que médicos e hospitais tenham acesso a mais dados de saúde dos pacientes, esses dados podem colaborar para um diagnóstico mais preciso e o ecossistema da saúde obtém avanços tecnológicos que contribuem para uma melhor gestão dos dados e combate as novas doenças.In the digital transformation scenario in which all sectors of activity are inserted, to improve efficiency, productivity and reduce time and costs, it is necessary to invest in new technologies. New technologies such as Internet of Things (IoT) and Blockchain are being developed to improve processing efficiency, the creation of business opportunities, requirements regulation, security and transparency and information decentralization, and are likely to be the next disruptive technologies that have transformed the various sectors of activity. In turn, the health sector has confronted difficulties with the emergence of new diseases and needs to transform and reinvent itself in order to maintain its legitimacy and continue to fulfill its obligations to citizens. The implementation of new technologies is one of the most effective approaches to increase efficiency, security, management, big data analysis and data performance. Because of this, this project proposes a Blockchain and IOT framework model applied to health. The implementation includes the creation of an application (ie, patients) and a website (ie, doctors, hospitals, pharmacies, public health), the data shared by users is stored on the blockchain connected to the application and access to the Blockchain is released by smart contracts. The aim of the suggested model is that the data is decentralized and allows access to all those connected to the blockchain. And in order not to infringe on the protection of patients' personal data, care has been taken that the patient user is the “owner” of all his data and shares it with any health entity he wishes. To achieve the objectives was applied a validation methodology by concept of the proposed model. The validation of the model concept was divided into five stages, followed by a qualitative analysis of the semi-structured interviews conducted with patients, doctors and health managers. As a result of the concept validation, it was observed that the opinion of all interviewees is that the implementation of the proposed model is advantageous and may contribute to advances in the health ecosystem. Therefore, once doctors and hospitals have access to more patients health data, these data can collaborate for a more accurate diagnosis and the health ecosystem obtains technological advances that contribute to better data management and to fight new diseases.info:eu-repo/semantics/publishedVersio

Cybersecurity and the Digital Health: An Investigation on the State of the Art and the Position of the Actors

Cybercrime is increasingly exposing the health domain to growing risk. The push towards a strong connection of citizens to health services, through digitalization, has undisputed advantages. Digital health allows remote care, the use of medical devices with a high mechatronic and IT content with strong automation, and a large interconnection of hospital networks with an increasingly effective exchange of data. However, all this requires a great cybersecurity commitment—a commitment that must start with scholars in research and then reach the stakeholders. New devices and technological solutions are increasingly breaking into healthcare, and are able to change the processes of interaction in the health domain. This requires cybersecurity to become a vital part of patient safety through changes in human behaviour, technology, and processes, as part of a complete solution. All professionals involved in cybersecurity in the health domain were invited to contribute with their experiences. This book contains contributions from various experts and different fields. Aspects of cybersecurity in healthcare relating to technological advance and emerging risks were addressed. The new boundaries of this field and the impact of COVID-19 on some sectors, such as mhealth, have also been addressed. We dedicate the book to all those with different roles involved in cybersecurity in the health domain

IoT-Based Applications in Healthcare Devices

The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions